Listed below is a range of free massively open online courses (MOOCs) that complement Engineering Mathematics nicely, fitting many of the topics and concepts taught alongside the degree. These courses are taught to a high standard by renown academics and professionals and therefore it comes as no surprise that they are highly recommended. Looking to boost your CV, support your studies or explore an area of interest? Discover your next learning milestone:
Software Engineering and Data Science Cources
Courses to help you get stuck into the theory, learn a new language or develop data science skills.
Machine Learning & AI Courses
As a former lead at Google, Founder of DeepLearning.ai, Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University, Andrew Ng is the perfect candidate to teach machine learning. His vast and pioneering experience as an AI researcher will help to build you up from machine learning fundamentals through lectures and coding assignments in MATLAB. Alternatively check out his deep learning website below.
The following series of MOOCs are from Imperial College London's engineering department. The aim of these more focused classes is aimed to deepen understanding when mining big data mining for insights is. These courses cover the role of Linear Algebra and Multivariate Calculus in machine learning, particularly deep learning.
Traditional Engineering Courses
The following courses cover fundamental engineering disciplines.
Specialised Engineering Courses
These courses are more niche in their application or industry size but are equally interesting and accessible to an Engineering Mathematics student.
Books and Websites
Below is a list of free books courtesy of their author website that complements nicely the engineering maths degree.
Below are further academic writing and reference guides.
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